JIAO Quanjun
Professional Title：Associate Professor
Email：jiaoqj@aircas.ac.cn
JIAO Quanjun : Associate professor, working in Aerospace Information Research Institute, Chinese Academy of Sciences, Ph.D. The main research interests cover optical remote sensing techniques in vegetation parameters retrieval and its applications. He has more than 20 years of experience in vegetation remote sensing researching.
Vegetation remote sensing
2016's Outstanding Science and Technology Achievement Prize of the Chinese Acadenmy of Sciences(Major Contributor)
[1]Quanjun Jiao,Bing Zhang,Wenjiang Huang,Huichun Ye,Zhaoming Zhang,Binxiang Qian, Bohai Hu,Shenglei Wang. The potential of hue angle calculated based on multispectral reflectance for leaf chlorophyll content estimation,IEEE Transactions on Geoscience and Remote Sensing [J],2023,61,4408616,1-16.
[2]Quanjun Jiao,Sun Qi,Bing Zhang,Wenjiang Huang,Huichun Ye,Zhaoming Zhang,Xiao Zhang. A random forest algorithm for retrieving canopy chlorophyll content of wheat and soybean trained withPROSAILsimulations using adjusted average leaf angle. Remote Sensing [J],2022,14,98.
[3]Qi Sun,Quanjun Jiao,Liangyun Liu,Xinjie Liu,Xiaojin Qian,Xiao Zhang,Bing Zhang. Improving the retrieval of forest canopy chlorophyll content from meris dataset by introducing the vegetation clumping index,IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing [J],2021,14: 5515–5528,
[4]Qi Sun,Quanjun Jiao,Xiaojin Qian,Liangyun Liu,Xinjie Liu,Huayang Dai. Improving the retrieval of crop canopy chlorophyll content using vegetation index combinations, Remote Sensing [J],2021,13(3):470.
[5]Quanjun Jiao,Liangyun Liu,Jiangui Liu,Hao Zhang,Bing Zhang,Atmospherically resistant vegetation water indices using the 970-nm water absorption feature,Journal of Applied Remote Sensing [J],14(3),034504,2020.
[6]Quanjun Jiao,Zhang Bing,Liu Jiangui,Liu Liangyun. A novel two-step method for winter wheat-leaf chlorophyll content estimation using a hyperspectral vegetation index. International Journal of Remote Sensing [J],2014,35(21),7363–7375.
[7]Quanjun Jiao,Bing Zhang,Liangyun Liu,Zhenwang Li,Yuemin Yue,Yong Hu. Assessment of spatio-temporal variations in vegetation recovery after the Wenchuan earthquake using Landsat data. Natural Hazards[J],2014,70(2): 1309–1326.
